High Expression of SLC16A1 as a Biomarker to Predict Poor Prognosis of Urological Cancers

Abstract

Objective: Tumor metabolism has always been the focus of cancer research. SLC16A1, as a key factor in catalysis of monocarboxylate transport across the plasma membrane, has been found to be associated with the occurrence and metastasis of a variety of cancers, but its prognostic significance and mechanism in different tumors are still unclear.

Methods: Based on the gene expression matrix and clinical information of human cancer tissues acquired from TCGA and GTEX databases, the differential expression of SLC16A1 in different tumors and normal tissues was analyzed. To confirm the association between its expression, the mutation of MMRS gene, and the expression level of DNMTs. Univariate Cox regression was applied to analyze the association between SLC16A1 expression and patient prognosis. The effect of SLC16A1 expression on patient survival was examined by Kaplan Meier analysis. GSEA was used to identify related signaling pathways.

Results: The expression of SLC16A1 was differentially expressed in most tumors, especially in the urinary tract where it is commonly highly expressed, and differential expression of SLC16A1 in different clinical stages. SLC16A1 expression was significantly positively correlated with MMRS gene mutation and DNMTS expression. Moreover, high SLC16A1 expression was associated with poorer overall survival (OS) and progression-free survival (PFS) in urological cancers. In particular, the results of the enrichment analysis showed that SLC16A1 was associated with processes such as cell adhesion and many signaling pathways affecting cell cycle were significantly enriched in the group with high-expressed SLC16A1.

Conclusion: SLC16A1 expression was upregulated in urological cancer. SLC16A1 may promote tumor development by regulating the epigenetic process of urological cancer and demonstrated a great potential as a prognostic biomarker of urological cancer patients.

Keywords: SLC16A1; biological marker; cancer in urology; generic cancer; prognosis.

Figure 1

SLC16A1 expression levels in different types of human cancers. (A) Based on the TCGA database, the expression level of SLC16A1 between different cancers was analyzed using Timer 2.0; (B) The expression data of normal tissues in GTEX database were supplemented to analyze the expression levels of SLC16A1 in tumor tissues and normal tissues of different cancers. (C) SLC16A1 expression in each cell line obtained through the CCLE database. Immunohistochemical staining of SLC16A1 protein in (D) testicular cancer; (E) prostate cancer; (F) kidney cancer; (G) bladder uroepithelial cancer tissues and corresponding normal tissues was obtained from the HPA database. TCGA, Cancer Genome Atlas Project; GTEX, genotype tissue expression; HPA, Human Protein Atlas. ^*P < 0.05, ^**P < 0.01, ^***P < 0.001.

Figure 2

SLC16A1 expression correlates with different periods of urological cancer. SLC16A1 expression in (A) ACC, (B) BLCA, (C) KICH, (D) KIRC, (E) KIRP, (F) TGCT in different clinical stages and (G) PRAD in different Gleason.

Figure 3

SLC16A1 expression in urological cancers promotes MMRS mutations and DNMTs activity. SLC16A1 expression and (A) ML H1, MSH2, MSH6, PMS2, EpCAM mutations; (B) Correlation between DNMT1, DNMT2, DNMT3A and DNMT3b expression. Note: MMRS: DNA mismatch repair; DNMTs: DNA methyltransferase. ^*P < 0.05, ^**P < 0.01, ^***P < 0.001.

Figure 4

High SLC16A1 expression suggests a poor prognosis for urological cancer. Univariate Cox analysis of patients with different tumors (A) OS and (B) PFS; Kaplan Meier and timeROC analysis to detect the effect of SLC16A1 expression on OS in (C) ACC, (D) BLCA), (E) KICH, (F) KIRC, (G) KIRP, (H) PRAD, (I)TGCT patients and PFS in (J) ACC, (K) BLCA, (L) KICH, (M) KIRC, (N) KIRP, (O) PRAD, (P) TGCT patients. OS, total survival; PFS, progression-free survival; HR, Hazard ratio.

Figure 5

SLC16A1 expression is associated with carcinogenic signaling pathways. In GOChord plots showing the top 10 GO terms enriched in (A) BP, (B) CC, (C) MF and genes positively associated with SLC16A1; (D) bubble plots to show the top 10 pathways in KEGG analysis; GSEA analysis showing the set of (E) GO and (F) KEGG genes associated with SLC16A1 expression. GSEA, single gene set enrichment analysis; GO, Gene Ontology; BP, Bioengineering; CC, Cellular Component; MF, Molecular Function; KEGG, Kyoto Encyclopedia of Genes and Genomes.